To address the limitation that the traditional Automatic Emergency Braking(AEB) strategy based on Time To Collision (TTC) does not take into account the speed of the vehicle, this paper proposed a dynamic collision time threshold model that took into account the vehicle speed and an AEB control strategy based on dynamic collision time threshold was designed. In order to ensure the comfort and safety of the braking process, a two-stage braking strategy was determined and the deceleration rate was designed, using PI control to complete the vehicle deceleration control. The TTC thresholds for different vehicle speeds were determined through simulation and a dynamic crash time threshold model was established. Hardware-In-the-Loop (HIL) simulation results show that the AEB strategy designed in this paper improves the collision avoidance success rate by 47.6% compared with the traditional AEB strategy under the premise of ensuring comfort, thus has better comprehensive performance.

To improve the collision avoidance performance of the Autonomous Emergency Braking (AEB) system in dangerous braking scenarios, this paper proposed an AEB control strategy considering the braking intention of the front vehicle and its test and evaluation method. A joint platform of PreScan, Simulink, and driving simulator was established to collect drivers’ braking operation data, classify the braking intention of the front car based on K-means clustering method, and use sliding time window to extract intention recognition model to train the dataset. The front car uses a double-layer hidden Markov model to identify the driver’s braking intention, while the main car calculates the critical safety distance threshold based on different braking intentions and performs collision avoidance control. A PreScan+Simulink virtual simulation and test environment was established, and AEB strategy comprehensive evaluation method was proposed based on Analytic Hierarchy Process (AHP). Four typical AEB control models were compared, which verified that the proposed method can timely trigger braking to avoid collisions in different braking scenarios, while reducing driving discomfort caused by premature braking.

In order to improve the prediction accuracy of State Of Charge (SOC) of power batteries, this paper proposed a method to improve the traditional ampere-hour intergral method to estimate the SOC of the lithium-ion battery based on a single particle Li diffusion model. The solver programs for estimating SOC with traditional and improved ampere-hour integration method and communication interface programs for battery data acquisition were written in software LabVIEW, which achieved the on-line monitoring of the battery SOC under different environmental temperatures and currents by the two methods. The results show that, under the above discharging conditions, the maximum estimation errors of the improved method and the traditional ampere-hour integral method are 1.11% and 1.89%, respectively. When the discharge current changes dramatically, the battery SOC estimated by the improved method fluctuates less than the traditional ampere-hour integral method.

Based on the test platform of volume constant combustion bomb, the influence of geometrical parameters of the premixed single-orifice active pre-chamber on the ignition characteristics of the pre-chamber were investigated by the combustion visualization method. During the pressure constant combustion process in the early stage of flame development, the time from the start of ignition until the flame area reaches half of the visible window area of the combustion vessel is defined as the initial flame development time, which is used as a reference index to measure the ignition effect of the active pre-chamber under different geometrical parameters: under the test conditions of different orifice diameters (2.0~4.0 mm), different inner diameters of the pre-chamber channel (3.0~5.5 mm), and different open angles of the lower end (0°~75°), the maximal differences of initial flame development time are 9.3 ms, 6.8 ms, and 2.9 ms, respectively. Therefore, the effect of the three geometrical parameters on the ignition effect of the single-orifice active pre-chamber are, in descending order, the orifice diameter, the inner diameter of the pre-chamber channel and the opening angle of the lower end of the pre-chamber.

To address combustion and emission issues in the lean combustion of gasoline direct injection (GDI) engine, ethanol-doped reformate gas was used to enhance the engine’s performance. The CONVERGE three-dimensional simulation technology was employed to explain the engine’s performance at a microscopic level. The results show that introducing ethanol-doped reformate gas can improve the distribution of equivalence ratio in the cylinder, promote the generation of H radicals and OH radicals, facilitating effective combustion. With an increase in the doping ratio of reforming gas, the distribution range and concentration of HO₂ and H₂O₂ become wider and higher, and the stratification phenomenon in the combustion chamber becomes more pronounced. As the doping ratio of reforming gas increases to 20%, the peak values of in-cylinder soot generation mass and number density are reduced by 90% and 56.25%, respectively, effectively improving the soot emissions of GDI engines.

In order to improve the NVH performance of the timing housing of a gasoline engine specific for a range extender, several support bosses were added locally to the timing housing, which significantly improves the dynamic stiffness of the timing housing, and at the same time effectively reduces the vibration response and deformation per unit of excitation, so as to reduce the noise of the range extender assembly 1 m from the engine front-end side in the full-load acceleration condition by 4.0 dB(A), the linearity of the noise SPL and the acceleration of the vibration of the timing housing were significantly improved. The validation results show that improving the dynamic stiffness can effectively improve the noise radiation from the structural vibration of thin-walled parts.

In order to study the overdrive control of vehicle driven by hub-motor, this paper started from steering control, independent driving control, and joint control of two systems, analyzed the research progress of steering stability control strategy. It firstly classified the aspects affecting the stability based on the steering control technology, then analyzed the characteristics of hierarchical control structure and centralized control structure, as well as the stability research based on different control structures. Finally, combined with the research status and technical progress of the improvement of vehicle operating stability driven by hub motors, the paper predicated future trend.

To optimize the fuel economy and auxiliary power battery performance of hydrogen fuel cell hybrid vehicles, this article proposed an energy management strategy based on Twin Delayed Deep Deterministic policy gradient with Prioritized Experience Replay (TD3-PER). Adopting the Twin Delayed Deep Deterministic policy gradient (TD3) algorithm, it achieves more accurate continuous control while preventing training over estimation. By combining the Prioritized Experience Replay (PER) algorithm, the training of the strategy is accelerated while achieving better optimization performance. The simulation results show that compared with the Deep Deterministic Policy Gradient (DDPG) algorithm, the proposed TD3-PER energy management strategy reduces hydrogen consumption by 5.47% per 100 kilometers and average power fluctuation by 6.49%.

The Remaining Useful Life (RUL) prediction accuracy of lithium battery is not high because the selected health factors are not ideal. To solve this problem, this paper proposed a data-driven remaining useful life estimation approach for lithium-ion batteries based on charging health feature optimization. Firstly different health factors were selected in the battery charging process, then, a two-step feature selection method based on maximum information coefficient was used to obtain optimal health factors. Finally, the Attention Temporal Convolutional Network (ATCN) mechanism was used to predict the remaining useful life of the battery. The proposed lithium battery RUL prediction framework was validated by a study of NASA’s lithium battery aging data and compared with other modeling methods including Simple Recurrent Neutral Network (SimpleRNN), Long Short Term Memory (LSTM) neutral network and Gate Recurrent Unit (GRU) neutral network. The experimental results indicate the proposed method has achieved optimal prediction results in all the datasets.

To maximize the regenerative braking energy as the goal, the paper puts forward a new energy commercial vehicle regenerative braking control strategy, through the analysis of the regenerative braking system structure and principle, front and rear braking force distribution, motor and battery power constraints, under the premise that guarantees braking direction stability, reasonably distribute the braking force. The simulation model of commercial vehicle regenerative braking system was established by AMESim to simulate and verify the control strategy. Finally, the control strategy in this paper was tested and verified by the chassis dynamometer. The results show that the designed control strategy can greatly save the energy consumption of new energy commercial vehicles and extend the driving range.